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Update parameters of rSPDEobj1d objects

Source: R/stationary1d.R
update.rSPDEobj1d.Rd

Function to change the parameters of a rSPDEobj1d object

Usage

# S3 method for class 'rSPDEobj1d'
update(
  object,
  user_nu = NULL,
  user_alpha = NULL,
  user_kappa = NULL,
  user_tau = NULL,
  user_sigma = NULL,
  user_range = NULL,
  user_theta = NULL,
  user_m = NULL,
  loc = NULL,
  graph = NULL,
  parameterization = NULL,
  type_rational_approximation = object$type_rational_approximation,
  ...
)

Arguments

object

The covariance-based rational SPDE approximation, computed using matern.rational()

user_nu

If non-null, update the shape parameter of the covariance function. Will be used if parameterization is 'matern'.

user_alpha

If non-null, update the fractional SPDE order parameter. Will be used if parameterization is 'spde'.

user_kappa

If non-null, update the parameter kappa of the SPDE. Will be used if parameterization is 'spde'.

user_tau

If non-null, update the parameter tau of the SPDE. Will be used if parameterization is 'spde'.

user_sigma

If non-null, update the standard deviation of the covariance function. Will be used if parameterization is 'matern'.

user_range

If non-null, update the range parameter of the covariance function. Will be used if parameterization is 'matern'.

user_theta

For non-stationary models. If non-null, update the vector of parameters.

user_m

If non-null, update the order of the rational approximation, which needs to be a positive integer.

loc

The locations of interest for evaluating the model.

graph

An optional metric_graph object.

parameterization

If non-null, update the parameterization.

type_rational_approximation

Which type of rational approximation should be used? The current types are "chebfun", "brasil" or "chebfunLB".

...

Currently not used.

Value

It returns an object of class "rSPDEobj1d". This object contains the same quantities listed in the output of matern.rational().

See also

simulate.rSPDEobj1d(), matern.rational()

Examples


s <- seq(from = 0, to = 1, length.out = 101)
kappa <- 20
sigma <- 2
nu <- 0.8
r <- sqrt(8*nu)/kappa #range parameter
op_cov <- matern.rational(loc = s, nu = nu, range = r, sigma = sigma, m = 2, 
parameterization = "matern")
cov1 <- op_cov$covariance(ind = 1)
op_cov <- update(op_cov, user_range = 0.2)
cov2 <- op_cov$covariance(ind = 1)
plot(s, cov1, type = "l")
lines(s, cov2, col = 2)